Optimization of SVM parameters for recognition of regulatory DNA sequences

DOI10.1007/S11750-010-0152-XzbMath1204.92031OpenAlexW2018979222WikidataQ57601522 ScholiaQ57601522MaRDI QIDQ621732

Robertas Damaševičius

Publication date: 28 January 2011

Published in: Top (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11750-010-0152-x

zbMATH Keywords

bioinformaticsmachine learningsupport vector machinepromoter recognitionSVM parameter optimization

Mathematics Subject Classification ID

Applications of mathematical programming (90C90) Numerical optimization and variational techniques (65K10) Learning and adaptive systems in artificial intelligence (68T05) Biochemistry, molecular biology (92C40)

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Cites Work

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• Efficient optimization of support vector machine learning parameters for unbalanced datasets
• Optimal parameter selection in support vector machines
• A Simplex Method for Function Minimization
• Choosing multiple parameters for support vector machines

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